
import os
import unittest

from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class    _snake_case (						UpperCAmelCase_	,    unittest.TestCase				):
 __lowerCAmelCase	:  int	   =      LxmertTokenizer
 __lowerCAmelCase	:  Any	   =      LxmertTokenizerFast
 __lowerCAmelCase	:  Dict	   =      True
 __lowerCAmelCase	:  List[Any]	   =      True


 def   lowercase__  (       self):


   '''simple docstring'''




   super().setUp()

   lowercase__	: Tuple     		=   [
       """[UNK]""",
       """[CLS]""",
       """[SEP]""",
       """want""",
       """##want""",
       """##ed""",
       """wa""",
       """un""",
       """runn""",
       """##ing""",
       """,""",
       """low""",
       """lowest""",
   ]
   lowercase__	: str     		=   os.path.join(self.tmpdirname       ,	VOCAB_FILES_NAMES["""vocab_file"""])
   with open(self.vocab_file       ,	"""w"""       ,	encoding="""utf-8""") as vocab_writer:
     vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]))


 def   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__	: Optional[Any]     		=   """UNwant\u00E9d,running"""
   lowercase__	: Union[str, Any]     		=   """unwanted, running"""
   return input_text, output_text


 def   lowercase__  (       self):


   '''simple docstring'''




   lowercase__	: Dict     		=   self.tokenizer_class(self.vocab_file)

   lowercase__	: List[Any]     		=   tokenizer.tokenize("""UNwant\u00E9d,running""")
   self.assertListEqual(SCREAMING_SNAKE_CASE_       ,	["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""])
   self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_)       ,	[7, 4, 5, 10, 8, 9])



 def   lowercase__  (       self):


   '''simple docstring'''




   if not self.test_rust_tokenizer:
     return

   lowercase__	: Tuple     		=   self.get_tokenizer()
   lowercase__	: Dict     		=   self.get_rust_tokenizer()

   lowercase__	: List[Any]     		=   """I was born in 92000, and this is falsé."""

   lowercase__	: List[str]     		=   tokenizer.tokenize(SCREAMING_SNAKE_CASE_)
   lowercase__	: Any     		=   rust_tokenizer.tokenize(SCREAMING_SNAKE_CASE_)
   self.assertListEqual(SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_)

   lowercase__	: int     		=   tokenizer.encode(SCREAMING_SNAKE_CASE_       ,	add_special_tokens=SCREAMING_SNAKE_CASE_)
   lowercase__	: Union[str, Any]     		=   rust_tokenizer.encode(SCREAMING_SNAKE_CASE_       ,	add_special_tokens=SCREAMING_SNAKE_CASE_)
   self.assertListEqual(SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_)

   lowercase__	: Tuple     		=   self.get_rust_tokenizer()
   lowercase__	: List[Any]     		=   tokenizer.encode(SCREAMING_SNAKE_CASE_)
   lowercase__	: Dict     		=   rust_tokenizer.encode(SCREAMING_SNAKE_CASE_)
   self.assertListEqual(SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_)








from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType




class 			UpperCAmelCase_     (					_A	):


  '''simple docstring'''







  a__       			=						["""image_processor""", """tokenizer"""]
  a__       			=						"""BridgeTowerImageProcessor"""
  a__       			=						("""RobertaTokenizer""", """RobertaTokenizerFast""")
  def __init__(					self     :					Optional[Any]     ,				UpperCamelCase__     :					str     ,				UpperCamelCase__     :					Any       )     ->      Optional[int]:







    """simple docstring"""






    super().__init__(UpperCamelCase__     ,				UpperCamelCase__       )
  def __call__(					self     :					Optional[int]     ,				UpperCamelCase__     :					Tuple     ,				UpperCamelCase__     :					Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None     ,				UpperCamelCase__     :					bool = True     ,				UpperCamelCase__     :					Union[bool, str, PaddingStrategy] = False     ,				UpperCamelCase__     :					Union[bool, str, TruncationStrategy] = None     ,				UpperCamelCase__     :					Optional[int] = None     ,				UpperCamelCase__     :					int = 0     ,				UpperCamelCase__     :					Optional[int] = None     ,				UpperCamelCase__     :					Optional[bool] = None     ,				UpperCamelCase__     :					Optional[bool] = None     ,				UpperCamelCase__     :					bool = False     ,				UpperCamelCase__     :					bool = False     ,				UpperCamelCase__     :					bool = False     ,				UpperCamelCase__     :					bool = False     ,				UpperCamelCase__     :					bool = True     ,				UpperCamelCase__     :					Optional[Union[str, TensorType]] = None     ,				**UpperCamelCase__     :					Dict     ,				)     ->      BatchEncoding:







    """simple docstring"""






    __magic_name__								=			self.tokenizer(
        text=UpperCamelCase__     ,				add_special_tokens=UpperCamelCase__     ,				padding=UpperCamelCase__     ,				truncation=UpperCamelCase__     ,				max_length=UpperCamelCase__     ,				stride=UpperCamelCase__     ,				pad_to_multiple_of=UpperCamelCase__     ,				return_token_type_ids=UpperCamelCase__     ,				return_attention_mask=UpperCamelCase__     ,				return_overflowing_tokens=UpperCamelCase__     ,				return_special_tokens_mask=UpperCamelCase__     ,				return_offsets_mapping=UpperCamelCase__     ,				return_length=UpperCamelCase__     ,				verbose=UpperCamelCase__     ,				return_tensors=UpperCamelCase__     ,				**UpperCamelCase__     ,				)
    # add pixel_values + pixel_mask
    __magic_name__								=			self.image_processor(
        UpperCamelCase__     ,				return_tensors=UpperCamelCase__     ,				do_normalize=UpperCamelCase__     ,				do_center_crop=UpperCamelCase__     ,				**UpperCamelCase__       )
    encoding.update(UpperCamelCase__       )

    return encoding
  def 				_lowercase				(					self     :					Optional[Any]     ,				*UpperCamelCase__     :					Optional[Any]     ,				**UpperCamelCase__     :					str       )     ->      str:







    """simple docstring"""






    return self.tokenizer.batch_decode(*UpperCamelCase__     ,				**UpperCamelCase__       )
  def 				_lowercase				(					self     :					Dict     ,				*UpperCamelCase__     :					int     ,				**UpperCamelCase__     :					Optional[Any]       )     ->      str:







    """simple docstring"""






    return self.tokenizer.decode(*UpperCamelCase__     ,				**UpperCamelCase__       )





  @property
  def 				_lowercase				(					self     :					Tuple       )     ->      Union[str, Any]:







    """simple docstring"""






    __magic_name__								=			self.tokenizer.model_input_names
    __magic_name__								=			self.image_processor.model_input_names
    return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names       )       )

